Huang Zhujun, Lee Ryong-Gyu, Cuniberto Edoardo, Song Jiyoon, Lee Jeongwon, Alharbi Abdullah, Kisslinger Kim, Taniguchi Takashi, Watanabe Kenji, Kim Yong-Hoon, Shahrjerdi Davood
Electrical and Computer Engineering, New York University, Brooklyn, New York 11201, United States.
School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Daejeon, Yuseong-gu 34141, Korea.
ACS Nano. 2024 Oct 22;18(42):28700-28711. doi: 10.1021/acsnano.4c06929. Epub 2024 Sep 28.
Single-crystal hexagonal boron nitride (hBN) is used extensively in many two-dimensional electronic and quantum devices, where defects significantly impact performance. Therefore, characterizing and engineering hBN defects are crucial for advancing these technologies. Here, we examine the capture and emission dynamics of defects in hBN by utilizing low-frequency noise (LFN) spectroscopy in hBN-encapsulated and graphene-contacted MoS field-effect transistors (FETs). The low disorder of this heterostructure allows the detection of random telegraph signals (RTS) in large device dimensions of 100 μm at cryogenic temperatures. Analysis of gate bias- and temperature-dependent LFN data indicates that RTS originates from a single trap species within hBN. By performing multispace density functional theory (MS-DFT) calculations on a gated defective hBN/MoS heterostructure model, we assign substitutional carbon atoms in boron sites as the atomistic origin of RTS. This study demonstrates the utility of LFN spectroscopy combined with MS-DFT analysis on a low-disorder all-vdW FET as a powerful means for characterizing the atomistic defects in single-crystal hBN.
单晶六方氮化硼(hBN)广泛应用于许多二维电子和量子器件中,其中缺陷会显著影响器件性能。因此,表征和调控hBN缺陷对于推动这些技术的发展至关重要。在此,我们通过在hBN封装和石墨烯接触的MoS场效应晶体管(FET)中利用低频噪声(LFN)光谱,研究了hBN中缺陷的俘获和发射动力学。这种异质结构的低无序性使得在低温下能够在100μm的大尺寸器件中检测到随机电报信号(RTS)。对栅极偏置和温度相关的LFN数据的分析表明,RTS源自hBN中的单一陷阱种类。通过对带栅极缺陷的hBN/MoS异质结构模型进行多空间密度泛函理论(MS-DFT)计算,我们将硼位点上的替代碳原子确定为RTS的原子起源。这项研究证明了在低无序全范德华FET上结合LFN光谱和MS-DFT分析作为表征单晶hBN中原子缺陷的有力手段的实用性。